Application of cuckoo optimization algorithm–artificial neural network method of zinc oxide nanoparticles–chitosan for extraction of uranium from water samples

• Published in: Chemometrics and intelligent laboratory systems Vol. 135; pp. 70 - 75
• Main Authors: Khajeh, Mostafa, Jahanbin, Elham
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.07.2014
• Subjects: Artificial neural network–cuckoo optimization algorithm; Uranium; Water samples; Zinc oxide nanoparticles–chitosan; Zinc oxide nanoparticles–chitosan; Uranium; Artificial neural network–cuckoo optimization algorithm; Water samples
• ISSN: 0169-7439; 1873-3239
• DOI: 10.1016/j.chemolab.2014.04.003

In this study, a solid phase extraction using the new sorbent (zinc oxide nanoparticles–chitosan) has been developed for preconcentration and determination of trace amount of uranium from water samples. Hybrid modeling of cuckoo optimization algorithm–artificial neural network (COA–ANN) has been employed to develop the model for simulation and optimization of this method. The 1-(2-pyridylazo)-2-naphthol (PAN) was used as chelating agent. The pH, volume of elution solvent, mass of zinc oxide nanoparticles–chitosan, concentration of PAN, flow rate of sample and elution solvent were the input variables, while recovery of uranium was the output. At the optimum conditions, the limit of detections and enrichment factor were 0.5μgL−1 and 125, respectively for the uranium. The developed procedure was then applied to the extraction and determination of uranium from water samples. •Uranium is extensively used in the nuclear industry and is highly radioactive.•The nanoparticles have large specific area and internal diffusion resistance is absence.•The nanoparticles have a higher efficiency for the removal of analyte.•The ANN–COA was used to optimize the extraction percent of analyte.